Search Results (50)

In marine seismic surveys, the indistinguishability of subsurface boundaries caused by the superimposition of the acoustic signals reflected from it, particularly at specific frequency ranges characterized by strong spectral interference, reduces the resolution of the seismic record. We processed sub-bottom profiler data, acquired using a Bubble Pulser (nominal central frequency: ~400 Hz; effective bandwidth extending to ~1 kHz), (i) by extracting continuous wavelet transform (CWT) coefficients at the dominant energy scale to form the envelope and (ii) by applying Hilbert-based instantaneous frequency analysis to characterize medium-dependent spectral shifts. Envelope accuracy was benchmarked against four conventional filters using the sum of squared error (SSE) relative to a cubic-spline reference. CWT yielded the lowest SSE, outperforming low-pass 1 kHz and band-pass 400–1000 Hz; band-pass 400–650 Hz and low-pass 650 Hz were the least effective. Instantaneous-frequency trends differentiated rock, sand, and mud layers. Thus, compared to fixed-band filters, the scale-adaptive CWT envelope replicates raw energy more faithfully, while frequency attributes improve sediment classification. Low-pass filtering at 1000 Hz provides a more accurate representation of energy distribution than does bandpass filtering, particularly in the 400–650 Hz range. The integrated workflow—a robust, parameter-light alternative for high-resolution stratigraphic interpretation—enhances offshore engineering safety. Full article

Community detection in complex networks plays a pivotal role in modern scientific research, including in social network analysis and protein structure analysis. Traditional community detection methods face challenges in integrating heterogeneous multi-source information, capturing global semantic relationships, and adapting to dynamic network evolution. This paper proposes a novel unsupervised multimodal community detection algorithm (UMM) based on fractal iteration. The core idea is to design a dual-channel encoder that comprehensively considers node semantic features and network topological structures. Initially, node representation vectors are derived from structural information (using feature vectors when available, or singular value decomposition to obtain feature vectors for nodes without attributes). Subsequently, a parameter-free graph convolutional encoder (PFGC) is developed based on fractal iteration principles to extract high-order semantic representations from structural encodings without requiring any training process. Furthermore, a semantic–structural dual-channel encoder (DC-SSE) is designed, which integrates semantic encodings—reduced in dimensionality via UMAP—with structural features extracted by PFGC to obtain the final node embeddings. These embeddings are then clustered using the K-means algorithm to achieve community partitioning. Experimental results demonstrate that the UMM outperforms existing methods on multiple real-world network datasets. Full article

Background: Salmonella is a bacterium that causes foodborne infections. This study characterized two strains isolated from cheese and beef in Brazil using whole-genome sequencing (WGS). Objectives: We evaluated their antimicrobial resistance profiles, virulence factors, plasmid content, serotypes and phylogenetic relationships. Methods: DNA was extracted and sequenced on the NovaSeq 6000 platform; the pangenome was assembled using the Roary tool; and the phylogenetic tree was constructed via IQ-TREE. Results and Discussion: For contextualization and comparison, 3493 Salmonella genomes of Brazilian origin from NCBI were analyzed. In our isolates, both strains carried the aac(6′)-Iaa_1 gene, while only Schwarzengrund harbored the qnrB19_1 gene and the Col440I_1 plasmid. Cerro presented the islands SPI-1, SPI-2, SPI-3, SPI-4, SPI-5 and SPI-9, while Schwarzengrund also possessed SPI-13 and SPI-14. Upon comparison with other Brazilian genomes, we observed that Cerro and Schwarzengrund represented only 0.40% and 2.03% of the national database, respectively. Furthermore, they revealed that Schwarzengrund presented higher levels of antimicrobial resistance, a finding supported by the higher frequency of plasmids in this serovar. Furthermore, national data corroborated our findings that SPI-13 and SPI-14 were absent in Cerro. A virulence analysis revealed distinct profiles: the cdtB and pltABC genes were present in the Schwarzengrund isolates, while the sseK and tldE1 family genes were exclusive to Cerro. The results indicated that the sequenced strains have pathogenic potential but exhibit low levels of antimicrobial resistance compared to national data. The greater diversity of SPIs in Schwarzengrund explains their prevalence and higher virulence potential. Conclusions: Finally, the serovars exhibit distinct virulence profiles, which results in different clinical outcomes. Full article

This study investigates the temporal dynamics, sources, and photochemical behaviour of key volatile organic compounds (VOCs) along Marylebone Road, London (1 January 2015–1 January 2023), a heavily trafficked urban area. Hourly measurements of benzene, toluene, ethylbenzene, ethene, propene, isoprene, propane, and ethyne, alongside ozone (O₃) and meteorological data, were analysed using correlation matrices, regression, cross-correlation, diurnal/seasonal analysis, wind-sector analysis, PCA (Principal Component Analysis), and clustering. Strong inter-VOC correlations (e.g., benzene–ethylbenzene: r = 0.86, R² = 0.75; ethene–propene: r = 0.68, R² = 0.53) highlighted dominant vehicular sources. Diurnal peaks of benzene, toluene, and ethylbenzene aligned with rush hours, while O₃ minima occurred in early mornings due to NO titration. VOCs peaked in winter under low mixing heights, whereas O₃ was highest in summer. Wind-sector analysis revealed dominant VOC emissions from SSW (south-southwest)–WSW (west-southwest) directions; ethyne peaked from the E (east)/ENE (east-northeast). O₃ concentrations were highest under SE (southeast)–SSE (south-southeast) flows. PCA showed 39.8% of variance linked to traffic-related VOCs (PC1) and 14.8% to biogenic/temperature-driven sources (PC2). K-means clustering (k = 3) identified three regimes: high VOCs/low O₃ in stagnant, cool air; mixed conditions; and low VOCs/high O₃ in warmer, aged air masses. Findings highlight complex VOC–O₃ interactions and stress the need for source-specific mitigation strategies in urban air quality management. Full article

Objective: This research seeks to investigate the effects of preoperative intense pulsed light with manual meibomian expression (IPL-MGX) on the refractive accuracy of cataract surgery on dry eyes with meibomian gland dysfunction (MGD-related dry eyes). Methods: Fifty-six MGD-related dry eye cases planned for cataract surgery were analyzed. IPL-MGX (four times at 2-week intervals) was performed before preoperative examination. Axial length (AL), anterior chamber depth (ACD), corneal curvature (mean-K), tear break-up time (TBUT), superficial punctate keratopathy in the central cornea (C-SPK), corneal higher-order aberrations (HOAs), and predicted postoperative spherical equivalent (P-SE) were evaluated pre- and post-IPL-MGX. The postoperative subjective spherical equivalent (S-SE) was evaluated after one month. The absolute difference between the S-SE and P-SE was considered an indication of P-SE accuracy. Changes in all the variables were assessed before and after IPL-MGX treatment. Results: No significant differences were observed in AL or ACD (p = 0.85, 0.56). The differences in mean-K, TBUT, C-SPK, and HOAs were significant (p < 0.01). P-SE accuracy based on post-IPL-MGX data was significantly higher than that based on pre-IPL-MGX data (p < 0.01). P-SE accuracy was within 0.25 diopters (D) in 14.3% of pre- and 55.4% of post-IPL-MGX, within 0.5D in 55.4% of pre- and 92.9% of post-IPL-MGX, within 0.75D in 98.2% of pre- and post-IPL-MGX, and within 1.0D in 98.2% of pre- and 100% of post-IPL-MGX. In the range of 0.25 and 0.5 D, the accuracy of P-SE was significantly higher in post-IPL-MGX (p < 0.01). Conclusions: Preoperative IPL-MGX considerably improved the predicted postoperative refraction accuracy in patients with MGD-related dry eye undergoing cataract surgery. Full article

Sand porosity is an important compactness parameter that influences the mechanical properties of sand. In order to evaluate the temporal variation in sand porosity, a new method of sand porosity evaluation based on the statistics of target sand particles (which refers to particles within a specific particle size range) is presented. The relationship between sand porosity and the number of target sand particles at the soil surface considering observation depth is derived theoretically, and it is concluded that there is an inverse relationship between the two. Digital image processing and the k-means clustering method were used to distinguish particles in digital images where particles may mask each other, and a criterion for determining the number of particles was proposed, that is, the criterion of min(Dao). The execution process was implemented by self-written codes using Python (2021.3). An experiment on a simple case of Go pieces and sand samples of different porosities was conducted. The results show that the sum of the squared error (SSE) in the k-means method can converge with a small number of iterations. Furthermore, there is a minimum value between the parameter Dao and the set value of a single-particle pixel, and the pixel corresponding to this value is a reasonable value of a single-particle pixel, that is, the min(Dao) criterion is proposed. The k-means method combined with the min(Dao) criterion can analyze the number of particles in different particle size ranges with occlusion between particles. The test results of sand samples with different densities show that the method is reasonable. Full article

Two-dimensional (2D) materials have shown outstanding potential for new devices based on their interesting electrical properties beyond conventional 3D materials. In recent years, new concepts such as the valley degree of freedom have been studied to develop valleytronics in hexagonal lattice 2D materials. We investigated the valley degree of freedom of GaX and Janus GaXY (X, Y = S, Se, Te). By considering the spin–orbit coupling (SOC) effect in the band structure calculations, we identified the Rashba-type spin splitting in band structures of Janus Ga₂SSe and Ga₂STe. Further, we confirmed that the Zeeman-type spin splitting at the K and K’ valleys of GaX and Janus Ga₂XY show opposite spin contributions. We also calculated the Berry curvatures of GaX and Janus GaXY. In this study, we find that GaX and Janus Ga₂XY have a similar magnitude of Berry curvatures, while having opposite signs at the K and K’ points. In particular, GaTe and Ga₂SeTe have relatively larger Berry curvatures of about 3.98 Ų and 3.41 Ų, respectively, than other GaX and Janus Ga₂XY. Full article

This study aimed to analyze the trend in land surface temperature (LST) over time using the entire archive of the available cloud-free Landsat images from 1986 to 2022 for Jordan and its nine local climate zones (LCZs). Two primary datasets were used (i) Landsat-5; -8 imagery, and (ii) map of LCZs of Jordan. All LST images were clipped, preprocessed, and checked for cloud contamination and bad pixels using the quality control bands. Then, time-series of monthly LST images were generated through compositing and mosaicking processes using cloud computing functions and Java scripts in Google Earth Engine (GEE). The Mann–Kendall (MK) test and Sen’s slope estimator (SSE) were used to detect and quantify the magnitude of LST trends. Results showed a warming trend in the maximum LST values for all LCZs while there was annual fluctuation in the trend line of the minimum LST values in the nine zones. The monthly average LST values showed a consistent upward trajectory, indicating a warming condition, but with variations in the magnitude. The annual rate of change in LST for the LCZs showed that the three Saharan zones are experiencing the highest rate of increase at 0.0184 K/year for Saharan Mediterranean Warm (SMW), 0.0185 K/year for Saharan Mediterranean Cool (SMC), and 0.0169 K/year for Saharan Mediterranean very Warm (SMvW), indicating rapid warming in these regions. The three arid zones came in the middle, with values of 0.0156 K/year for Arid Mediterranean Warm (AMW), 0.0151 for Arid Mediterranean very Warm (AMvW), and 0.0139 for Arid Mediterranean Cool (AMC), suggesting a slower warming trend. The two semi-arid zones and the sub-humid zone showed lower values at 0.0138, 0.0127, and 0.0117 K/year for the Semi-arid Mediterranean Cool (SaMC), Semi-arid Mediterranean Warm (SaMW) zones, and Semi-humid Mediterranean (ShM) zones, respectively, suggesting the lowest rate of change compared to other zones. These findings would provide an overall understanding of LST change and its impact in Jordan’s LCZs for sustainable development and water resources demand and management. Full article

Perishable commodities like cassava necessitate effective postharvest preservation for various industrial applications. Hence, optimizing pretreatment processes and modeling drying kinetics hold paramount importance. This study aimed to optimize cassava pretreatment using the central composite design of a response surface methodology while also assessing microstructure and dehydration kinetics. Diverse chemical and thermal pretreatments were explored, encompassing sodium metabisulfite concentrations (0–4% w/w), citric acid concentrations (0–4% w/w), and blanching time (0–4 min). The four investigated responses were moisture content, whiteness index, activation energy (E_a), and effective moisture diffusivity (D_eff). Employing five established drying models, suitability was appraised after optimal pretreatment conditions were determined. The findings revealed that moisture content ranged from 5.82 to 9.42% db, whereas the whiteness index ranged from 87.16 to 94.23. D_eff and E_a ranged from 5.06 × 10⁻⁹ to 6.71 × 10⁻⁹ m²/s and 29.65–33.28 kJ/mol, respectively. The optimal pretreatment conditions for dried cassava were identified by optimizing the use of 1.31% citric acid, 1.03% sodium metabisulfite, and blanching time for 1.01 min. The microstructure indicated that particular chemical and thermal pretreatment configurations yielded particles in the shape of circular and elliptical granules. The logarithmic model provided the most accurate description of the dehydration kinetics, with the highest R² value (0.9859) and the lowest χ², RSME, and SSE values of 0.0351, 0.0015, and 0.0123, respectively. Full article

In recent years, there has been rapid development in computer technology, leading to an increasing number of medical systems utilizing electronic medical records (EMRs) to store their clinical data. Because EMRs are very private, healthcare institutions usually encrypt these data before transferring them to cloud servers. A technique known as searchable encryption (SE) can be used by healthcare institutions to encrypt EMR data. This technique enables searching within the encrypted data without the need for decryption. However, most existing SE schemes only support keyword or range searches, which are highly inadequate for EMR data as they contain both textual and digital content. To address this issue, we have developed a novel searchable symmetric encryption scheme called SSE-RK, which is specifically designed to support both range and keyword searches, and it is easily applicable to EMR data. We accomplish this by creating a conversion technique that turns keywords and ranges into vectors. These vectors are then used to construct index tree building and search algorithms that enable simultaneous range and keyword searches. We encrypt the index tree using a secure K-Nearest Neighbor technique, which results in an effective SSE-RK approach with a search complexity that is quicker than a linear approach. Theoretical and experimental study further demonstrates that our proposed scheme surpasses previous similar schemes in terms of efficiency. Formal security analysis demonstrates that SSE-RK protects privacy for both data and queries during the search process. Consequently, it holds significant potential for a wide range of applications in EMR data. Overall, our SSE-RK scheme, which offers improved functionality and efficiency while protecting the privacy of EMR data, generally solves the shortcomings of the current SE schemes. Full article

This study focuses on investigating and comparing the influence of the surface functional groups and chemical matrices of macroporous resin on the Cr(III) exchange mechanism. The results discussed herein indicate that sulfonic resin removed Cr(III) ions with faster kinetics than carboxylic resin. Equilibrium was established within 15 and 7 min for the carboxylic and sulfonic resins, respectively, with a 99.5% removal efficiency at 333 K. The Langmuir exchange capacity was observed to be higher for the sulfonic resin (1.5 mmol∙g⁻¹) than the carboxylic resin (0.80 mmol∙g⁻¹) at 333 K. The adsorption isotherms obtained for the carboxylic and sulfonic resins were H and S types, respectively, representing a higher affinity of the carboxylic resin for Cr(III) removal at a low metal ion concentration. Additionally, it was noted that the carboxylic resin preferentially co-sorbed H⁺ and Cr(OH)²⁺ ions below Cr(III) concentrations of 6–8 mmol.L⁻¹. The H+ ions co-sorption was almost negligible, whereas the Cr(III) exchange was 87 and 34.5% for the carboxylic acid resin and sulfonic acid resins, respectively. The data of the concentration studies were evaluated using non-linear forms of Freundlich, Langmuir, and Dubinin–Radushkevich adsorption isotherm models, and the kinetic data were analyzed using pseudo-Ist- and pseudo-IIst-order kinetic models. The activation energy E_a for Amberlite IRC-50 (Na⁺) was greater (22.4 kJ∙mol⁻¹) than that of Amberlyst-15 (Na⁺) 17 kJ∙mol⁻¹, indicating a higher energy barrier for the ion exchange reaction on carboxylic resin. As per the findings of a statistical error analysis (RMSE and SSE) and absolute average relative distribution (AARD) statistical model, a close agreement between the experimental and theoretical values suggested that the Langmuir isotherm was well-fitted to the current adsorptive investigations. The interaction of the COO⁻ and SO³⁻ functional sites of the resins for the exchange of Cr(III) ions was validated through an FT-IR analysis. The macroporous resins used in the current study for Cr(III) exchange showed promising performances compared to other resins. The current investigations revealed valuable insights for choosing macroporous resins as adsorbents in water filtration systems. Full article

In this study, the influence of fiber particle size on the mechanical properties of a wood-–plastic composite (WPC) was investigated using a combination of experimental measurements and numerical modeling. Four different sizes of wood fibers (10–20 mesh, 20–40 mesh, 40–80 mesh, and 80–120 mesh) were used to reinforce high-density polyethylene (HDPE), either separately or in combination. The different sizes of fibers produced varying properties in the resulting composites. The smallest fiber size (80–120 mesh) resulted in the lowest flexural and tensile properties, but the highest impact strength (15.79 kJ/m²) compared to the other three sizes (12.18–14.29 kJ/m²). Using a blend of fiber sizes resulted in improved mechanical properties. Composites containing a mix of 20–40 mesh and 40–80 mesh fibers exhibited the best flexural (strength 74.16 MPa, modulus 5.35 GPa) and tensile performance (strength 48.27 MPa, modulus 4.30 GPa), while composites containing a mix of all four fiber sizes had the highest impact-resistant strength (16.08 kJ/m²). Several models, including the Rule of Mixtures (ROM), the Inverse Rule of Mixtures (IROM), and the Hirsch models, were used to predict the performance of WPCs. The ROM model was found to be the most accurate in describing the mechanical properties of WPCs reinforced with multi-size wood fibers, based on the sum squared error (SSE) analysis. Full article

Fair clustering aims to partition a dataset while mitigating bias in the original dataset. Developing fair clustering algorithms has gained increasing attention from the machine learning community. In this paper, we propose a fair k-means algorithm, fair first clustering (FFC), which consists of an initialization stage, a relaxation stage, and an improvement stage. In the initialization stage, k-means is employed to cluster each group. Then a combination step and a refinement step are applied to ensure clustering quality and guarantee almost fairness. In the relaxation stage, a commonly used fairness metric, balance, is utilized to assess fairness, and a threshold is set to allow for fairness relaxation while improving the clustering quality. In the improvement stage, a local search method is used to improve the clustering quality without changing the fairness. Comparisons of fairness and clustering quality are carried out between our method and other state-of-the-art fair clustering methods on 10 datasets, which include both synthetic and real-world datasets. The results show that compared to the method with the second highest balance value, FFC shares the same SSE value on one dataset and achieves lower SSE values on six datasets. Full article

Solar energy is considered a promising source of power generation in sub-Saharan Africa due to the high sunshine in these areas. Deploying decentralised solar-powered mini-grid systems to provide access to electricity in rural areas is fraught with difficulties in accurately predicting consumption, automatic monitoring, and operation sustainability to support the socio-economic conditions of rural communities. This study proposed SoAMIRural, which integrates solar PV mini-grid and advanced metering infrastructure for rural communities. SoAMIRural was implemented and tested for a case study community in Ghana. Solar PV Selection Equation Matrix (SPSEM) and Sample Size Equation (SSE) were used to determine the sustainable demand generation capacity of 24 kVA. Load estimations and need assessments were conducted to ascertain the rural community’s electric load and priority needs. SoAMIRural was evaluated with an error margin of 5%, resulting in 95% accuracy in energy consumption threshold management and monitoring to ensure energy conservation and sustainability of the mini-grid system. This study maps out a conceptual framework for a smart solar PV mini-grid system for rural communities and its advantages in realising SDG 7 in Ghana by 2030. Full article

Being the annihilation and creation operators on the space $\mathfrak{h}$ of square integrable Bernoulli functionals, quantum Bernoulli noises (QBN) satisfy the canonical anti-commutation relation (CAR) in equal time. Let $\mathcal{K}$ be the Hilbert space of an open quantum system interacting with QBN (the environment). Then $\mathcal{K}\otimes \mathfrak{h}$ just describes the coupled quantum system. In this paper, we introduce and investigate an interacting stochastic Schrödinger equation (SSE) in the framework $\mathcal{K}\otimes \mathfrak{h}$, which might play a role in describing the evolution of the open quantum system interacting with QBN (the environment). We first prove some technical propositions about operators in $\mathcal{K}\otimes \mathfrak{h}$. In particular, we obtain the spectral decomposition of the tensor operator $I_{\mathcal{K}}\otimes N$, where $I_{\mathcal{K}}$ means the identity operator on $\mathcal{K}$ and N is the number operator in $\mathfrak{h}$, and give a representation of $I_{\mathcal{K}}\otimes N$ in terms of operators $I_{\mathcal{K}}\otimes {\partial }_k^{\ast }{\partial }_k$, $k\ge 0$, where ${\partial }_k$ and ${\partial }_k^{\ast }$ are the annihilation and creation operators on $\mathfrak{h}$, respectively. Based on these technical propositions as well as Mora and Rebolledo’s results on a general SSE, we show that under some mild conditions, our interacting SSE has a unique solution admitting some regularity properties. Some other results are also proven. Full article